{"id":"https://openalex.org/W3117140649","doi":"https://doi.org/10.1109/hpec43674.2020.9286195","title":"Studying the Effects of Hashing of Sparse Deep Neural Networks on Data and Model Parallelisms","display_name":"Studying the Effects of Hashing of Sparse Deep Neural Networks on Data and Model Parallelisms","publication_year":2020,"publication_date":"2020-09-22","ids":{"openalex":"https://openalex.org/W3117140649","doi":"https://doi.org/10.1109/hpec43674.2020.9286195","mag":"3117140649"},"language":"en","primary_location":{"id":"doi:10.1109/hpec43674.2020.9286195","is_oa":false,"landing_page_url":"https://doi.org/10.1109/hpec43674.2020.9286195","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE High Performance Extreme Computing Conference (HPEC)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101457271","display_name":"Mohammad Hasanzadeh Mofrad","orcid":"https://orcid.org/0000-0003-4369-6928"},"institutions":[{"id":"https://openalex.org/I170201317","display_name":"University of Pittsburgh","ror":"https://ror.org/01an3r305","country_code":"US","type":"education","lineage":["https://openalex.org/I170201317"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Mohammad Hasanzadeh Mofrad","raw_affiliation_strings":["University of Pittsburgh, Pittsburgh, USA"],"affiliations":[{"raw_affiliation_string":"University of Pittsburgh, Pittsburgh, USA","institution_ids":["https://openalex.org/I170201317"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038997010","display_name":"Rami Melhem","orcid":"https://orcid.org/0000-0001-6403-5446"},"institutions":[{"id":"https://openalex.org/I170201317","display_name":"University of Pittsburgh","ror":"https://ror.org/01an3r305","country_code":"US","type":"education","lineage":["https://openalex.org/I170201317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rami Melhem","raw_affiliation_strings":["University of Pittsburgh, Pittsburgh, USA"],"affiliations":[{"raw_affiliation_string":"University of Pittsburgh, Pittsburgh, USA","institution_ids":["https://openalex.org/I170201317"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072934511","display_name":"Yousuf Ahmad","orcid":null},"institutions":[{"id":"https://openalex.org/I4210089979","display_name":"Carnegie Mellon University Qatar","ror":"https://ror.org/00az5dt38","country_code":"QA","type":"education","lineage":["https://openalex.org/I4210089979","https://openalex.org/I74973139"]}],"countries":["QA"],"is_corresponding":false,"raw_author_name":"Yousuf Ahmad","raw_affiliation_strings":["Carnegie Mellon University in Qatar, Doha, Qatar"],"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University in Qatar, Doha, Qatar","institution_ids":["https://openalex.org/I4210089979"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018894377","display_name":"Mohammad Hammoud","orcid":"https://orcid.org/0000-0002-5742-6147"},"institutions":[{"id":"https://openalex.org/I4210089979","display_name":"Carnegie Mellon University Qatar","ror":"https://ror.org/00az5dt38","country_code":"QA","type":"education","lineage":["https://openalex.org/I4210089979","https://openalex.org/I74973139"]}],"countries":["QA"],"is_corresponding":false,"raw_author_name":"Mohammad Hammoud","raw_affiliation_strings":["Carnegie Mellon University in Qatar, Doha, Qatar"],"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University in Qatar, Doha, Qatar","institution_ids":["https://openalex.org/I4210089979"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101457271"],"corresponding_institution_ids":["https://openalex.org/I170201317"],"apc_list":null,"apc_paid":null,"fwci":0.6839,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.72791894,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9976999759674072,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":0.9950000047683716,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7754947543144226},{"id":"https://openalex.org/keywords/data-parallelism","display_name":"Data parallelism","score":0.6080541610717773},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.5697659254074097},{"id":"https://openalex.org/keywords/speedup","display_name":"Speedup","score":0.5648981928825378},{"id":"https://openalex.org/keywords/cache","display_name":"Cache","score":0.5082058906555176},{"id":"https://openalex.org/keywords/sparse-matrix","display_name":"Sparse matrix","score":0.5032753348350525},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4597582519054413},{"id":"https://openalex.org/keywords/matrix-multiplication","display_name":"Matrix multiplication","score":0.43287724256515503},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.4227983355522156},{"id":"https://openalex.org/keywords/partition","display_name":"Partition (number theory)","score":0.4134894013404846},{"id":"https://openalex.org/keywords/parallelism","display_name":"Parallelism (grammar)","score":0.3542943000793457},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2960522770881653},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.17341339588165283},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09795603156089783}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7754947543144226},{"id":"https://openalex.org/C61483411","wikidata":"https://www.wikidata.org/wiki/Q3124522","display_name":"Data parallelism","level":3,"score":0.6080541610717773},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.5697659254074097},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.5648981928825378},{"id":"https://openalex.org/C115537543","wikidata":"https://www.wikidata.org/wiki/Q165596","display_name":"Cache","level":2,"score":0.5082058906555176},{"id":"https://openalex.org/C56372850","wikidata":"https://www.wikidata.org/wiki/Q1050404","display_name":"Sparse matrix","level":3,"score":0.5032753348350525},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4597582519054413},{"id":"https://openalex.org/C17349429","wikidata":"https://www.wikidata.org/wiki/Q1049914","display_name":"Matrix multiplication","level":3,"score":0.43287724256515503},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.4227983355522156},{"id":"https://openalex.org/C42812","wikidata":"https://www.wikidata.org/wiki/Q1082910","display_name":"Partition (number theory)","level":2,"score":0.4134894013404846},{"id":"https://openalex.org/C2781172179","wikidata":"https://www.wikidata.org/wiki/Q853109","display_name":"Parallelism (grammar)","level":2,"score":0.3542943000793457},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2960522770881653},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.17341339588165283},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09795603156089783},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C84114770","wikidata":"https://www.wikidata.org/wiki/Q46344","display_name":"Quantum","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/hpec43674.2020.9286195","is_oa":false,"landing_page_url":"https://doi.org/10.1109/hpec43674.2020.9286195","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE High Performance Extreme Computing Conference (HPEC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/8","score":0.47999998927116394,"display_name":"Decent work and economic growth"}],"awards":[{"id":"https://openalex.org/G7909653302","display_name":null,"funder_award_id":"CCF-1725657","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":54,"referenced_works":["https://openalex.org/W26556108","https://openalex.org/W1598993252","https://openalex.org/W1994371611","https://openalex.org/W2003840611","https://openalex.org/W2007259720","https://openalex.org/W2012313745","https://openalex.org/W2045271686","https://openalex.org/W2056999868","https://openalex.org/W2065607954","https://openalex.org/W2089437293","https://openalex.org/W2112796928","https://openalex.org/W2130942839","https://openalex.org/W2134237243","https://openalex.org/W2415655736","https://openalex.org/W2523246573","https://openalex.org/W2525778437","https://openalex.org/W2608554408","https://openalex.org/W2617766261","https://openalex.org/W2727953781","https://openalex.org/W2764043458","https://openalex.org/W2767979715","https://openalex.org/W2785452945","https://openalex.org/W2796347433","https://openalex.org/W2803210444","https://openalex.org/W2807147113","https://openalex.org/W2808133870","https://openalex.org/W2919115771","https://openalex.org/W2962736495","https://openalex.org/W2963351145","https://openalex.org/W2964004663","https://openalex.org/W2964336816","https://openalex.org/W2972087877","https://openalex.org/W2973134322","https://openalex.org/W2973727699","https://openalex.org/W2977720775","https://openalex.org/W2982392466","https://openalex.org/W2987484405","https://openalex.org/W2990176236","https://openalex.org/W2991040477","https://openalex.org/W2991043234","https://openalex.org/W3035574168","https://openalex.org/W3100809954","https://openalex.org/W3100839241","https://openalex.org/W3101584733","https://openalex.org/W3106161546","https://openalex.org/W4293584584","https://openalex.org/W4293775467","https://openalex.org/W4297689207","https://openalex.org/W6679436768","https://openalex.org/W6738460352","https://openalex.org/W6756379755","https://openalex.org/W6756718674","https://openalex.org/W6770317905","https://openalex.org/W6910447991"],"related_works":["https://openalex.org/W2950520577","https://openalex.org/W1554644772","https://openalex.org/W2003935582","https://openalex.org/W2494130044","https://openalex.org/W3170887803","https://openalex.org/W74409296","https://openalex.org/W3209384898","https://openalex.org/W1595834484","https://openalex.org/W1991844655","https://openalex.org/W2593878938"],"abstract_inverted_index":{"Deep":[0],"Neural":[1],"Network":[2],"(DNN)":[3],"training":[4],"and":[5,29,90,113,138,141,189,202,220,231],"inference":[6],"are":[7,12,54],"two":[8],"resource-intensive":[9,56],"tasks":[10],"that":[11,216],"usually":[13],"scaled":[14,195],"out":[15],"using":[16,71],"data":[17,22,28,72,89,95,101,112,137,188,219],"or":[18,73],"model":[19,30,74,91,114,139,190,221],"parallelism":[20,23,31,75,96],"where":[21],"parallelizes":[24,32],"over":[25,33],"the":[26,34,41,50,82,99,109,144,147,176,185],"input":[27,100,110],"network.":[35],"Also,":[36],"dense":[37,47,60],"matrix-matrix":[38],"multiplication":[39],"is":[40],"key":[42,83],"primitive":[43],"behind":[44],"training/inference":[45],"of":[46,108,128,146,187],"DNNs.":[48],"On":[49],"contrary,":[51],"sparse":[52,179,206],"DNNs":[53],"less":[55],"compared":[57],"to":[58,97,118,153,169,183,197,227],"their":[59,156],"counterparts":[61],"while":[62],"offering":[63],"comparable":[64],"accuracy.":[65],"Similarly,":[66],"they":[67],"can":[68],"be":[69,124],"parallelized":[70],"with":[76,208,217],"Sparse":[77],"Matrix-Matrix":[78],"Multiplication":[79],"(SpMM)":[80],"as":[81,121,163],"primitive.":[84],"To":[85],"scale":[86],"out,":[87],"both":[88],"parallelisms":[92,115,140,191,222],"initially":[93],"use":[94,175],"partition":[98],"among":[102],"multiple":[103],"machines.":[104],"This":[105],"initial":[106],"partitioning":[107],"makes":[111],"performance":[116,186],"prone":[117],"load":[119,157,171,229],"imbalance":[120,158],"partitions":[122],"may":[123],"imbalanced.":[125],"As":[126],"part":[127],"this":[129],"paper,":[130],"we":[131,160,174],"take":[132],"a":[133,164,204],"deeper":[134],"look":[135],"into":[136],"closely":[142],"study":[143],"mechanics":[145],"SpMM":[148],"used":[149],"for":[150],"each.":[151],"Moreover,":[152],"intuitively":[154],"remedy":[155],"problem,":[159],"incorporate":[161],"hashing":[162],"simple":[165],"yet":[166],"powerful":[167],"method":[168],"address":[170],"imabalance.":[172],"Finally,":[173],"IEEE":[177],"HPEC":[178],"DNN":[180,207],"challenge":[181],"dataset":[182],"evaluate":[184],"at":[192],"scale.":[193],"We":[194],"up":[196],"32":[198],"machines":[199],"(896":[200],"cores)":[201],"inferred":[203],"large":[205],"4B":[209],"parameters":[210],"in":[211],"51":[212],"seconds.":[213],"Results":[214],"suggest":[215],"hashing,":[218],"achieve":[223],"super-linear":[224],"speedup":[225],"due":[226],"better":[228],"balance":[230],"cache":[232],"utilization.":[233]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}